The present invention relates to engine diagnostics. More particularly, the invention is directed to a system and method for monitoring, analyzing and diagnosing internal combustion engine conditions using a starter motor as a sensor and employing spatial analysis techniques.
A wide range of on-board or off-board internal combustion (IC) diagnostic systems are employed in engine control systems for monitoring engine condition and performance. For example, the Ford OASIS and the General Motors car automotive maintenance (CAM) diagnostic systems employ existing sensors and computational resources, such as an Engine Control Unit (ECU). When acceptable conditions or tolerance limits are exceeded, in any of the sensed parameters, an annunciator or indicator is enabled. In some systems, such as the Ford OASIS the fault conditions may be stored and retrieved for subsequent off-board diagnostics. Avionics equipment also employ a variety of on-board implementations to sense failure conditions and also to indicate apparently operational ready conditions.
Conventional diagnostic systems require the use of a variety of temporarily connected or mounted sensors and interfacing devices. In addition, current diagnostic systems do not monitor condition and/or performance of internal engines, such as a Diesel Cycle (Compression Ignition) and Otto Cycle (Spark Ignition) engines. Most diagnostic and prognostic techniques rely upon intrusive techniques, such as cylinder compression, which interfere with normal engine operation and provide only static test information. In addition such techniques are costly and time-consuming.
As far as is known, only two research projects conducted at Purdue University and Wayne State University were directed towards developing dynamic, in-situ methods for determining internal engine operation and condition. These research projects were directed toward developing a method using a rotating disk having precisely machined teeth or lobes on its periphery and a crankshaft mounted to the disk. The disk, in turn, was mounted on the crankshaft. As the disk or flywheel was rotated, either a magnetic or Hall-Effect sensor was used to measure the instantaneous angular velocity, i.e., the crankshaft RPM, and time between passing of the successive teeth or lobes. Increased cost, as well as the smoothing or filtering effects of harmonic balancing, and the lack of capability to relate the acquired information to any specific cylinder, were just some of the deficiencies that led to the failure of the project. A similar implementation was developed within the then Bendix Automotive Sector, now Allied Signal, for sensing rough engine operation. This system also proved to be too costly and its operation proved unreliable in the hostile automotive environment.
It is therefore desirable to develop a reliable and relatively low cost non-intrusive on-board system and method that provides diagnostic and prognostic engine information, such as impending wear or failure conditions, and solves the aforementioned problems.
The present invention provides an internal engine diagnostic and prognostic system and method utilizing current, time and crank position data. The current supplied to a starter motor by a battery during engine start up is monitored using a current sensor and a representative starter motor current waveform is generated. In addition, crank position information is provided by a crank position sensor or derived from other sources, for example, the ECU, the fueling system or the ignition system.
The present invention uses the starter motor as both an actuator and a sensor. Consistent relationships between piston stroke and angular crankshaft rotation in an engine are used to spatially normalize the starter motor current waveform. Once spatial consistency has been established, the starter motor current waveform is reduced or deconvolved into its constituent parts, that is, subharmonics, fundamental and harmonic components. The deconvolved waveform components and derived and/or known engine parameters are then used to determine engine status and diagnostic information.
Prognostic and maintenance planning information is derived from the previously derived status and diagnostic information by applying Weibull techniques. Weibull techniques are well known statistical failure distributions that are used in engineering applications to determine and model the mechanical wear of a machine.